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Record W2144946055 · doi:10.1109/isspit.2006.270762

Breast Tumor Microwave Simulator Based on a Radar Signal Model

2006· article· en· W2144946055 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of CalgaryUniversity of Wisconsin-Madison
KeywordsMicrowave imagingBreast cancerRadarMicrowaveImaging phantomComputer scienceMammographyRadar imagingBreast imagingAntenna (radio)Breast tissueSIGNAL (programming language)ModalitiesAcousticsElectronic engineeringCancerRadiologyTelecommunicationsMedicinePhysicsEngineeringInternal medicine

Abstract

fetched live from OpenAlex

Breast cancer incidence in women has increased from one in twenty in 1960 to one in eight today. Although advances have improved the likelihood of early detection, current breast imaging modalities still have limitations. In recent years, microwave imaging has shown its potential as an alternative approach for breast cancer detection. The principle behind this approach is the detection of differences in electrical characteristics between normal and malignant breast tissues in the microwave frequency range. A novel simulation technique for radar breast microwave imagery is proposed in this paper. Dispersive effects in the propagation medium and different antenna radiation pattern sizes are included in the simulation model. The proposed method produced accurate results when compared to real data collected from a phantom that mimics the average differences in dielectric properties from skin, breast, and malignant tissue

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.178
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations14
Published2006
Admission routes2
Has abstractyes

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